Computational Intelligence in Intelligent Transportation Systems: An Overview

Hina, Manolo Dulva; Soukane, Assia; Ramdane-Chérif, Amar

doi:10.1007/978-3-030-78284-9_2

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…ITM initiatives must include smart-city governance, which develops planning techniques for improved laws. The social policy of innovative services is one of the critical tenets of the smart-city management system ( Hina, Soukane & Ramdane-Cherif, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Machine learning based IoT system for secure traffic management and accident detection in smart cities

Balasubramanian

Balaji

Munshi

et al. 2023

PeerJ Computer Science

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In smart cities, the fast increase in automobiles has caused congestion, pollution, and disruptions in the transportation of commodities. Each year, there are more fatalities and cases of permanent impairment due to everyday road accidents. To control traffic congestion, provide secure data transmission also detecting accidents the IoT-based Traffic Management System is used. To identify, gather, and send data, autonomous cars, and intelligent gadgets are equipped with an IoT-based ITM system with a group of sensors. The transport system is being improved via machine learning. In this work, an Adaptive Traffic Management system (ATM) with an accident alert sound system (AALS) is used for managing traffic congestion and detecting the accident. For secure traffic data transmission Secure Early Traffic-Related EveNt Detection (SEE-TREND) is used. The design makes use of several scenarios to address every potential problem with the transportation system. The suggested ATM model continuously modifies the timing of traffic signals based on the volume of traffic and anticipated movements from neighboring junctions. By progressively allowing cars to pass green lights, it considerably reduces traveling time. It also relieves traffic congestion by creating a seamless transition. The results of the trial show that the suggested ATM system fared noticeably better than the traditional traffic-management method and will be a leader in transportation planning for smart-city-based transportation systems. The suggested ATM-ALTREND solution provides secure traffic data transmission that decreases traffic jams and vehicle wait times, lowers accident rates, and enhances the entire travel experience.

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Section: Introductionmentioning

confidence: 99%

Machine learning based IoT system for secure traffic management and accident detection in smart cities

Balasubramanian

Balaji

Munshi

et al. 2023

PeerJ Computer Science

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show abstract

“…Therefore, ITSs seek to improve resource management and increase people's convenience through information services and alerts [Dalarmelina et al 2020]. Therefore, this improvement contributes to facilitating flow in the city, reducing time spent in congestion, reducing fuel consumption, CO2 emissions and monetary losses [Hina et al 2022, Meneguette et al 2012, Lourenco et al 2019.…”

Section: Introductionmentioning

confidence: 99%

An Action Application for Improving Social Security Using GPS and Internet Events

Shinzato,

Filho,

Nakamura

et al. 2023

JER

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In recent years there has been a huge increase in the number of cars and consequently the people who use them. This way, applications related to Intelligent Transport Systems play a key role in driver safety and have been gaining ground to assist with issues related to accidents, congestion and traffic problems. Given the above, this work proposes an application to capture data on events that are taking place in the city, disseminating these events to citizens who can take some action to try to minimize the amount of congestion that may occur due to an event on some road.

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Autonomous Vehicles and Intelligent Transportation Systems—A Framework of Intelligent Vehicles

Tyagi

Sreenath

2022

Disruptive Technologies and Digital Transformations for Society 5.0

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Computational Intelligence in Intelligent Transportation Systems: An Overview

Cited by 6 publications

References 27 publications

Machine learning based IoT system for secure traffic management and accident detection in smart cities

Machine learning based IoT system for secure traffic management and accident detection in smart cities

An Action Application for Improving Social Security Using GPS and Internet Events

Autonomous Vehicles and Intelligent Transportation Systems—A Framework of Intelligent Vehicles

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